v2.3.0 release - #16
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- Modified frames.py to add a clipping stage to confidence using IQR, so a single sharp FFT peak cannot dominate the overall average. - Modified frames.py to used median instead of sum for bucket weight aggregation so weight doesn't scale with frame count.
- Modified frames.py to use median absolute deviation instead of inter- quartile range when determining clipping bounds.
- Modified tests/unit/test_frames.py to add test checking that new confidence clipping logic is able to counter outlier confidence ratios. - Modified tests/fixtures.py to pass amplitude/noise_std to write_synthetic_frame so tests can write frames with data that will result in a spiked confidence ratio.
- Modified README.md to outline confidence clipping strategy.
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